Soft Consensus Models in Group Decision Making

  • Ignacio Javier Perez
  • Francisco Javier Cabrerizo
  • Sergio Alonso
  • Francisco Chiclana
  • Enrique Herrera-Viedma
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 339)


In group decision making problems, when a consensual solution is required, a natural question is how to measure the closeness among experts’ opinions in order to obtain the consensus level. To do so, different approaches have been proposed. Following this research line, several authors have introduced hard consensus measures varying between 0 (no consensus or partial consensus) and 1 (full consensus or complete agreement). However, consensus as a full and unanimous agreement is far from being achieved in real situations. So, in practice, a more realistic approach is to use some softer consensus measures, which assess the consensus degree in a more flexible way reflecting better all possible partial agreements obtained through the process. The aim of this chapter is to identify and describe the different existing approaches to compute soft consensus measures in fuzzy group decision making problems. Additionally, we analyze the current models and new challenges on this field.



This paper has been developed with the financing of FEDER funds in TIN2013-40658-P and Andalusian Excellence Project TIC-5991.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Ignacio Javier Perez
    • 1
  • Francisco Javier Cabrerizo
    • 2
  • Sergio Alonso
    • 3
  • Francisco Chiclana
    • 4
  • Enrique Herrera-Viedma
    • 5
  1. 1.Department of Computer Sciences and EngineeringUniversity of CadizPuerto RealSpain
  2. 2.Department of Software Engineering and Computer SystemsDistance Learning University of SpainMadridSpain
  3. 3.Department of Software EngineeringUniversity of GranadaGranadaSpain
  4. 4.Faculty of Technology, Centre for Computational IntelligenceDe Montfort UniversityLeicesterUK
  5. 5.Department of Computer Science and Artificial IntelligenceUniversity of GranadaGranadaSpain

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